<html><head><title>Plot Diagnostics for an plsone Object</title>
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<table width="100%"><tr><td>plot.plsone(plstools)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
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<h2>Plot Diagnostics for an plsone Object</h2>


<h3>Description</h3>

<p>
Nine plots (selectable by which.plot) are currently available:
Observed vs Expected values, Normal QQ-plot of residuals,
Representation of components th, Prediction vs the <i>h^{th}</i> component,
Representation of DModXN, Representation of Weights,
Representation of DModYN, Representationof Hotellin T2,
Representation of correlations with the conponents.
</p>


<h3>Usage</h3>

<pre>
## S3 method for class 'plsone':
plot(x, xax = 1, yax = 2, mfrow = NULL, which.plot =1:9,...)
</pre>


<h3>Arguments</h3>

<table summary="R argblock">
<tr valign="top"><td><code>x</code></td>
<td>
an object of class inheriting from 'plsone'</td></tr>
<tr valign="top"><td><code>xax</code></td>
<td>
the column number for the x-axis</td></tr>
<tr valign="top"><td><code>yax</code></td>
<td>
the column number for the y-axis</td></tr>
<tr valign="top"><td><code>mfrow</code></td>
<td>
a vector of the form 'c(nr,nc)', otherwise computed by as special
own function n2mfrow</td></tr>
<tr valign="top"><td><code>which.plot</code></td>
<td>
a numeric vector containing the numbers of The selected plots
(see details)</td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
further arguments passed to or from other methods.</td></tr>
</table>

<h3>Details</h3>

<p>
The selected plots are drawn on a graphics device.<br>
1: Observed vs Expected values<br>
2: Normal QQ-plot of residuals<br>
3: Representation of Components th (in 2 dimensions, by default xax=1 and yax=2).<br>
4: Prediction vs the <i>h^{th}</i> component (by default xax=1).<br>
5: Representation of DModXN<br>
6: Representation of Weights (in 2 dimensions, by default xax=1 and yax=2).<br>
7: representation of DModYN<br>
8: Representationof Hotellin T2<br>
9: Representation of correlations with the conponents
(in 2 dimensions, by default xax=1 and yax=2) <br>
</p>


<h3>Value</h3>

<p>
x is invisibly returned.</p>

<h3>References</h3>

<p>
Tenenhaus M.(1998) La Regression PLS. Theorie et pratique. Technip, Paris.<br>
</p>


<h3>See Also</h3>

<p>
<code><a href="plsone.html">plsone</a></code>, <code><a onclick="findlink('stats', 'qqnorm.html')" style="text-decoration: underline; color: blue; cursor: hand">qqnorm</a></code>,
<code><a onclick="findlink('ade4', 's.arrow.html')" style="text-decoration: underline; color: blue; cursor: hand">s.arrow</a></code>,
<code><a onclick="findlink('ade4', 's.label.html')" style="text-decoration: underline; color: blue; cursor: hand">s.label</a></code>, <code><a onclick="findlink('stats', 'plot.lm.html')" style="text-decoration: underline; color: blue; cursor: hand">plot.lm</a></code>
</p>


<h3>Examples</h3>

<pre>
require(pls)
data(yarn)
plstest &lt;- plsone(density ~ NIR, nf=6, data = yarn,scale=FALSE)
plot(plstest)
plot(plstest,which.plot=1:2)
plot(plstest,which.plot=c(1:2,6))
</pre>

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